Evaluation of oil shale resources based on geochemistry and logging in Tuanyushan, Qaidam Basin, Northwest China

In this study, oil shale resources in the Middle Jurassic Shimengou Formation in the Tuanyushan area along the northern margin of the Qaidam Basin in Northwest China are evaluated. The total organic carbon (TOC) content of oil shale in the study area is positively correlated with resistivity and neg...

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Bibliographic Details
Published in:Oil shale (Tallinn, Estonia : 1984) Estonia : 1984), 2020-09, Vol.37 (3), p.188-206
Main Authors: Wang, Jun-Xian, Sun, Ping-Chang, Liu, Zhao-Jun, Xu, Yin-Bo, Li, Li
Format: Article
Language:English
Subjects:
Acoustics
Analysis
Carbon
Correlation analysis
Electric properties
Electrical resistivity
Evaluation
Geochemistry
Hydrocarbons
Identification
Jurassic
Jurassic period
Methods
Mudstone
Neural networks
Oil shale
Oil shales
Organic carbon
Prediction models
Regression analysis
Regression models
Resources
Sedimentary rocks
Shale oil
Shale oils
Total organic carbon
Travel
Travel time
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Summary:In this study, oil shale resources in the Middle Jurassic Shimengou Formation in the Tuanyushan area along the northern margin of the Qaidam Basin in Northwest China are evaluated. The total organic carbon (TOC) content of oil shale in the study area is positively correlated with resistivity and negatively correlated with acoustic travel time and natural gamma. Based on TOC and oil yield, as well as the log response differences between the resistivity logging curve, the natural gamma logging curve and the acoustic travel time logging curve of mudstone with differing TOC contents, [DELTA]logR and stepwise regression models can be created to quantitatively determine the TOC content of oil shale. The results of the two prediction models and the measured values show the mean absolute deviation (MAD) of the [DELTA]logR model to be 0.95 wt% and the coefficient of determination, [R.sup.2], 0.67. The MAD of the stepwise regression model is 1.15 wt% and [R.sup.2] is 0.54. Of these two prediction models, the [DELTA]logR model has a higher recognition ability, but the predicted results are easily disturbed by silty mudstone. Therefore, the stepwise regression model is used to quantitatively identify oil shale resources in the study area. The comparison of the predicted and measured oil yields of oil shale from exploratory wells shows their [R.sup.2] to be 0.49. This suggests that in the whole study area, oil shale resources can be identified by the logging curve. Based on log interpretation, the volume method is used to estimate the area's oil shale resources. The results show the oil shale resources in this area to total 392 million tons and converted shale oil resources 24 million tons. Keywords: Qaidam Basin, Middle Jurassic, Shimengou Formation oil shale, logging prediction, quantitative evaluation.
ISSN:0208-189X
1736-7492
DOI:10.3176/oil.2020.3.02